code: def assert_design_soundness_two_sample(
      self, dtype, min_num_samples, min_discrepancy
  ):
      thresholds = [
          1e-5,
          1e-2,
          1.1e-1,
          0.9,
          1.0,
          1.02,
          2.0,
          10.0,
          1e2,
          1e5,
          1e10,
      ]
      rates = [1e-6, 1e-3, 1e-2, 1.1e-1, 0.2, 0.5, 0.7, 1.0]
      false_fail_rates, false_pass_rates = np.meshgrid(rates, rates)
      false_fail_rates = false_fail_rates.flatten().astype(dtype=dtype)
      false_pass_rates = false_pass_rates.flatten().astype(dtype=dtype)
  
      detectable_discrepancies = []
      for false_pass_rate, false_fail_rate in zip(
          false_pass_rates, false_fail_rates
      ):
          [sufficient_n1, sufficient_n2] = min_num_samples(
              thresholds,
              false_fail_rate=false_fail_rate,
              false_pass_rate=false_pass_rate,
          )
  
          detectable_discrepancies.append(
              min_discrepancy(
                  n1=sufficient_n1,
                  n2=sufficient_n2,
                  false_fail_rate=false_fail_rate,
                  false_pass_rate=false_pass_rate,
              )
          )
  
      detectable_discrepancies_ = self.evaluate(
          detectable_discrepancies
      )
      for discrepancies, false_pass_rate, false_fail_rate in zip(
          detectable_discrepancies_, false_pass_rates, false_fail_rates
      ):
          below_threshold = discrepancies <= thresholds
          self.assertAllEqual(
              np.ones_like(below_threshold, np.bool_),
              below_threshold,
              msg="false_pass_rate({}), false_fail_rate({})".format(
                  false_pass_rate, false_fail_rate
              ),
          )
          bound_tight = thresholds <= discrepancies * 2
          self.assertAllEqual(
              np.ones_like(bound_tight, np.bool_),
              bound_tight,
              msg="false_pass_rate({}), false_fail_rate({})".format(
                  false_pass_rate, false_fail_rate
              ),
          )
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 10 for calling the StatisticalTestingTest obj's underlying member method code with example usage: obj.assert_design_soundness_two_sample(dtype, min_num_samples, min_discrepancy) without return types